This article discusses the development and validation of radiomics models for differentiating between inverted papilloma and chronic rhinosinusitis with polyps using unenhanced CT images.…
Browsing: Radiomics
This article discusses a radiomic and machine learning approach to predict high- and low-risk thymoma using imaging features and clinical characteristics. The study aims…
This article discusses the development of a model using multimodal MRI, radiomics, and deep learning to predict the treatment response in cervical cancer patients…
This Special Issue focuses on introducing novel machine learning and deep learning approaches for the management of pediatric medulloblastoma, a type of brain tumor.…
This article discusses the integration of digital radiology and AI-driven radiomics in healthcare, specifically in the field of precision medicine. It explores the potential…
This study investigated the stability of MRI-based radiomics features in a rectal cancer cohort of 81 patients when generating features from both anatomical MRI…
This observational study assessed the utility of radiomics in differentiating between benign and malignant lung nodules detected on computed tomography (CT) scans. Employing random…
This study presents IRON, an integrative radiogenomic framework to predict the volumetric response of heterogeneous, multi-site ovarian cancer to NACT. The framework uses two…
This study examined the use of radiomic features extracted from initial CT images before TKI-PD-1 treatment to predict the response of hepatocellular carcinoma (HCC)…
The global Radiomics Market is projected to grow at a formidable rate in the forecast period, 2018-2028, due to the growing prevalence of various…